Cooked millet prolamin peptide for inhibiting alpha-amylase and alpha-glucosidase

ABSTRACT

A cooked millet prolamin peptide for inhibiting α-amylase and α-glucosidase, an application thereof, and a screening method thereof are disclosed. The sequence of the peptide is selected from SEQ ID NOS: 1-6. The peptide provided in the present disclosure can effectively inhibit the activities of α-glucosidase and α-amylase simultaneously and is safe and non-toxic and has no side effects. Therefore, the peptide has a good potential and application prospect as a functional component in food, health products, and hypoglycemic drugs.

CROSS REFERENCE TO THE RELATED APPLICATIONS

This application is based upon and claims priority to Chinese Patent Application No. 202210396241.7, filed on Apr. 15, 2022, the entire contents of which are incorporated herein by reference.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted in XML format via EFS-Web and is hereby incorporated by reference in its entirety. Said XML copy is named GBNYDX001-PKG_Sequence_Listing.xml, created on Jan. 31, 2023, and is 33,330 bytes in size.

TECHNICAL FIELD

The present disclosure belongs to the field of proteins. Specifically, the present disclosure provides a plurality of cooked millet prolamin peptides for inhibiting α-amylase and α-glucosidase, an application thereof, and a screening method thereof.

BACKGROUND

Diabetes has become a globally prevalent metabolic disease and is mainly manifested by metabolic disorders of body fat, carbohydrates, and proteins caused by increased blood glucose levels. The prevalence of diabetes has been steadily increasing in recent years. Non-insulin-dependent diabetes, i.e., type 2 diabetes, is common in people of all ages, and 90% of patients with diabetes have been diagnosed with type 2 diabetes. Dietary starch can be digested by α-amylase to produce a large amount of maltose which is then digested by α-glucosidase to form glucose. Elevated blood glucose levels caused by the rapid degradation of starch into glucose are referred to as postprandial hyperglycemia, which is an essential indicator of type 2 diabetes. Therefore, postprandial blood glucose can be controlled by inhibiting α-amylase and α-glucosidase to reduce the rate of carbohydrate hydrolysis to glucose. Currently available drugs for treating type 2 diabetes, such as metformin, acarbose, voglibose, and miglitol, can inhibit the activities of α-amylase and α-glucosidase, but the intake of these hypoglycemic drugs also has some side effects, such as flatulence and diarrhea.

In recent years, many foodborne peptides have been proven to have antibacterial properties, functions of lowering blood pressure and cholesterol, and antithrombotic and antioxidant activities. Food proteins have received much attention as a major source of functional peptides. Millet prolamin has been proven to have a good function in improving blood glucose metabolism. In other words, after millet prolamin is intragastrically administrated to diabetic mice, the millet prolamin is digested in the gastrointestinal tract and hydrolyzed to amino acids and peptides which enter the blood circulation to play physiological roles such as lowering blood glucose levels. Presently, the peptides for antioxidant, anti-inflammatory, and lipase inhibition have been isolated from millet prolamin, but there is a lack of research on millet prolamin hypoglycemic peptides. Therefore, it is necessary to explore peptide fragments in the small-molecular peptides obtained from the hydrolysis of millet prolamin which can be used as potential functional hypoglycemic substances.

SUMMARY

Given the above problems, in one aspect, the present disclosure provides a cooked millet prolamin peptide for inhibiting α-amylase and α-glucosidase. The sequence of the peptide is selected from SEQ ID NOS: 1-6.

Further, the sequence of the peptide is shown in SEQ ID NO: 1 or SEQ ID NO: 2.

In another aspect, the present disclosure provides a composition, and the composition includes the peptide described above and an acceptable excipient for pharmaceutical, food, or health products.

In another aspect, the present disclosure provides a use of the peptide or the composition described above in the preparation of α-amylase and/or α-glucosidase inhibitors.

In another aspect, the present disclosure provides an application of the peptide or the composition described above in the preparation of drugs for the treatment of diabetes.

In another aspect, the present disclosure provides an application of the peptide or the composition described above in the preparation of hypoglycemic food or health products suitable for diabetic populations.

Further, the diabetes is type 2 diabetes.

In another aspect, the present disclosure provides a method for screening the peptide, and the method includes:

-   -   (1) in vitro simulated digestion: hydrolyzing cooked millet         prolamin by enzymolysis to obtain protein hydrolysate;     -   (2) screening: conducting an ultrafiltration process of the         protein hydrolysate, performing a mass spectrometry sequencing         to obtain the peptide fragment sequences with high confidence         coefficient from an ultrafiltration grade component, carrying         out a virtual screening of the peptide fragment sequences by         Dock 6.9 software, screening peptide fragments with good docking         effects with α-glucosidase and α-amylase, respectively,         according to the grid score and the internal repulsion energy of         the peptide fragments, and comparing the peptide fragments with         good docking effect with α-glucosidase and the peptide fragments         with good docking effect with α-amylase to obtain the peptide         fragments with good docking effects with both α-glucosidase and         α-amylase;     -   (3) active site analysis and in vitro function prediction:         docking the peptide sequences obtained by screening in paragraph         [0015] with α-amylase and α-glucosidase, respectively, by Dock         6.9 software to determine the key amino acids and interaction         forces between the peptide sequences and α-amylase and         α-glucosidase, and conducting a prediction of the properties,         such as water solubility, instability, isoelectric point,         half-life period, and ADMET (Absorption, Distribution,         Metabolism, Elimination and Toxicity), of the screened peptide         sequences with good docking effects with both α-glucosidase and         α-amylase.

Further, pepsin and pancreatin enzyme are used in hydrolysis.

Further, the ultrafiltration grade component is less than 3 kDa.

Advantages:

In the present disclosure, six small peptides unreported before, namely, QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK, were screened from cooked millet prolamin for the first time, which can effectively inhibit the activities of α-glucosidase and α-amylase simultaneously. The structures of the small peptides QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK were also defined. At the same time, the six small peptides QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK have the advantages of safety, non-toxicity, and no side effects. Therefore, the peptides have a good potential and application prospect as a functional component in food, health products, and hypoglycemic drugs.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1D show the clocking result of QQLRPF with α-glucosidase and the docking result of QQLRPF with α-amylase.

FIGS. 2A-2D show the docking result of AGAGPQGRP with α-glucosidase and the docking result of AGAGPQGRP with α-amylase.

FIGS. 3A-3D show the docking result of FALQGAAFLGSA with α-glucosidase and the docking result of FALQGAAFLGSA with α-amylase.

FIGS. 4A-4D show the docking result of QQQQLLR with α-glucosidase and the docking result of QQQQLLR with α-amylase.

FIGS. 5A-5D show the docking result of KTGSGAEGMHGGK with α-glucosidase and the docking result of KTGSGAEGMHGGK with α-amylase.

FIGS. 6A-6D show the docking result of KAHAALGAK with α-glucosidase and the docking result of KAHAALGAK with α-amylase.

FIG. 7 shows the inhibition rates of QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK for α-glucosidase.

FIG. 8 shows the inhibition rates of QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK for α-amylase.

DETAILED DESCRIPTION OF THE EMBODIMENTS Embodiment 1: Extraction of Cooked Millet Prolamin

The millet was first ground into powder and sifted through a 60-mesh sieve. The resulting millet powder was dispersed in n-hexane at a ratio of 1:5 (w/v), followed by shaking in a water bath at 37° C. for 4 h and allowing the solution to stand. After the resulting millet powder and the n-hexane were stratified, the upper layer of n-hexane was discarded, and the lower layer of precipitate was collected and dried in a fume hood for 24 h to completely remove the n-hexane to obtain raw millet powder. The degreased raw millet powder and distilled water were mixed evenly at a ratio of 1:5 (w/v) and gelatinized for 10 min in a boiling water bath. The resulting precipitate was dried in an oven at 43° C. for 24 h and then powdered and sifted through a 60-mesh sieve to obtain cooked millet powder. The cooked millet powder was dispersed in a 70% ethanol solution at a ratio of 1:7 (m/v), followed by shaking in a water bath oscillator at 40° C. for 2 h. The resulting reaction solution was centrifuged at 7000 rpm for 10 min, and the resulting supernatant was collected and dialyzed in a dialysis bag for 24 h. The distilled water was replaced 4 times during dialysis. After dialysis, the resulting dialysate was centrifuged at 7000 rpm for 5 min, and the resulting precipitate was collected and lyophilized to obtain the cooked millet prolamin with a protein content of 85%.

Embodiment 2: In vitro Simulated Digestion of Cooked Millet Prolamin

The cooked millet prolamin sample was mixed with distilled water at a ratio of 1:5 (w/v), the pH was adjusted to 3, and 2000 U/mL of pepsin was added. After reacting for 2 h, the pH was adjusted to 7. Pancreatin enzyme was added at a concentration of 100 U trypsin per 1 mL of digestive fluid. The reaction was continued for 2 h. After the reaction was over, the enzyme was deactivated in a boiling water bath for 10 min to terminate the reaction. Finally, the precipitate was collected by centrifugation at 7000 rpm for 10 min to obtain the hydrolysate of digested protein.

Embodiment 3: Ultrafiltration of the In Vitro Simulated Digestion Products of Cooked Millet Prolamin

First, an Amicon®Ultra-15 centrifugal filter was pre-cleaned with ultra-pure water and dried after pre-cleaning. The centrifugal filter with a separation molecular weight of 3 kDa was selected and added with a sample of no more than 15 mL. The filter device covered with a lid was put into a centrifugal rotor for rotation for about 30 min at a rotational speed of 5000×g. After centrifugation, the lid and filter were removed, and the liquid in the centrifuge tube was collected and lyophilized to obtain the protein hydrolysate ultrafiltration sample less than 3 kDa.

Embodiment 4: Mass Spectrometry Sequencing and Screening of the In Vitro Simulated Digestion Products of Cooked Millet Prolamin

The components of the hydrolysate less than 3kDa were subjected to mass spectrometry sequencing by an electrospray-combined ion trap Orbitrap mass spectrometer, and the peptide sequences were analyzed by a de novo method to obtain all the peptide sequences with high confidence coefficient. Then, the peptides obtained by sequencing, based on the arid score of less than −115 kcal/mol and the internal repulsion energy of less than 30 kcal/mol, were virtually screened with α-glucosidase and α-amylase, respectively, by Dock 6.9 software. The screening results are shown in Table 1 and Table 2. Comparing Table 1 and Table 2, it can be found that small peptides QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK have better docking effects with both α-glucosidase and α-amylase.

TABLE 1 Peptides with good docking effect with α-amylase in virtual screening Internal Van der Electrostatic repulsion Grid score Waals force force energy SEQ ID NO: Sequence (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) 5 KTGSGAEG −152.065 −121.745 −30.3203 29.821 MHGGK 7 TLFDGHAA −148.936 −126.699 −22.2371 29.4055 LGAK 8 TSGAAGN −143.316 −135.542 −7.7739 26.7281 GVDAFGQ 3 FALQGAAF −136.847 −123.049 −13.7978 29.7369 LGSA 9 THVKKQQ −128.936 −103.875 −25.0614 28.0828 6 KAHAALG −128.263 −104.742 −23.5212 27.4757 AK 4 QQQQLLR −121.389 −99.6055 −21.7838 25.4738 1 QQLRPF −121.306 −101.535 −19.7709 27.2623 2 AGAGPQG −117.658 −96.1684 −21.4899 22.6545 RP 10 FQQFRP −116.577 −96.8112 −19.7656 20.0226 11 QQLLLPW −115.605 −96.7665 −18.8383 25.6813

TABLE 2 Peptides with good docking effect with α-glucosidase in virtual screening Internal Van der Electrostatic repulsion Grid score Waals force force energy SEQ ID NO: Sequence (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) 3 FALQGAAFL −155.651 −144.458 −11.1934 27.7357 GSA 5 KTGSGAEG −152.479 −133.221 −19.258 28.0528 MHGGK 12 GPAGHVKN −150.991 −127.832 −23.1587 29.119 Q 13 TMAALGAK −149.691 −117.439 −32.2518 28.3463 6 KAHAALGA −143.263 −106.148 −37.1147 23.8761 K 14 QGGPAGGR −141.531 −133.419 −8.1117 19.6846 P 15 GPAGPQGPR −136.794 −105.012 −31.7815 24.5535 16 PSLVRGPR −133.187 −107.608 −25.5786 28.0496 2 AGAGPQGR −130.089 −100.711 −29.3784 29.2749 P 17 AGPAGRP −122.886 −100.843 −22.0428 21.737 18 TNRFKP −122.602 −96.4056 −26.1962 23.5706 19 QQLLAPW −121.941 −118.523 −3.4175 29.6769 20 FTSSKPF −121.645 −97.7482 −23.8968 29.2416 1 QQLRPF −121.178 −106.425 −14.7534 23.4919 21 THEGQMSP −120.728 −110.295 −10.4326 23.9988 22 FSWTPR −120.695 −105.678 −15.0169 24.4493 23 YGVTHPCG −120.033 −105.671 −14.3625 22.4862 24 YAMTPR −119.305 −91.846 −27.4588 27.7076 4 QQQQLLR −119.111 −95.3296 −23.781 24.5052 25 FYWTPR −118.513 −105.079 −13.4341 28.163 26 QQFYPF −115.064 −107.588 −7.4758 26.6875

Embodiment 5: Molecular Docking and In Vitro Function Prediction of Hypoglycemic Peptides Screened from Millet Prolamin

Precise molecular docking analysis was further conducted using Dock 6.9 software to identify the active sites of QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK interacted with α-glucosidase and α-amylase. As shown from FIG. 1A to FIG. 1B, the interaction between QQLRPF and α-amylase was analyzed and it was found that QQLRPF forms hydrophobic interactions with residues Trp 59, Leu 165, Trp 58, Try 62, Ile 235, and His 305 of α-amylase, forms hydrogen bonds with residues His 305 and Gln 63 of α-amylase, and forms salt bridges, i.e., ionic bonds, with residues Glu 233 and His 101 of α-amylase. The interaction between QQLRPF and α-glucosidase was analyzed and it was found that QQLRPF forms hydrophobic interactions with residues Trp 481, Ala 555, Trp 516, Trp 376, Leu 677, Leu 678, Leu 650, Phe 297, Val 334, Ala 343, and Thr 339 of α-glucosidase, forms hydrogen bonds with Thr 339, Arg 429, Glu 427, Gly 399, Asn 301, Gly 651, and Ser 676 of α-glucosidase, forms salt bridges with Asp 282, Asp 616, and Glu 377 of α-glucosidase, and forms π-π stacking with Phe 649 of α-glucosidase (from FIG. 1C to FIG. 1D). As shown from FIG. 2A to FIG. 2B, AGAGPQGRP forms salt bridges with residues Arg 195, His 299, and Asp 356 of α-amylase, and forms hydrogen bonds with residues Leu 237, Glu 233, and His 201 of α-amylase, and forms hydrophobic interactions with Tyr 62, Trp 58, Ile 235, and Leu 165 of α-amylase. In addition, AGAGPQGRP forms a salt bridge with residue His 105 of α-glucosidase, forms hydrophobic interactions with Tyr 65 and Phe 166 of α-glucosidase, and forms hydrogen bonds with Lys 225 and Gly 228 (from FIG. 2C to FIG. 2D). As shown from FIG. 3A to FIG. 3B, FALQGAAFLGSA forms hydrophobic interactions with residues Tyr 151, Leu 165, Tyr 62, Trp 58, Trp 59, and Ile 51 of α-amylase, forms a salt bridge with Lys 200 of α-amylase, forms hydrogen bonds with His 305, Asp 300, Thr 163, Tyr 52, and Gln 63 of α-amylase, forms π-cation interaction with Trp 357 of α-amylase, and forms π-π stacking with Tyr 62 of α-amylase. Analysis of the interaction between FALQGAAFLGSA and α-glucosidase reveals that FALQGAAFLGSA forms hydrophobic interactions with residues Thr 203, Phe 166, Phe 147, Lys 398, Val 335, and Glu 377 of α-glucosidase, forms salt bridges with Glu 271 and His 304 of α-glucosidase, and forms hydrogen bonds with Gly 228 and Ala 348 of α-glucosidase (from FIG. 3C to FIG. 3D). As shown from FIG. 4A to FIG. 4B, QQQQLLR forms hydrogen bonds with residues Asp 353, Asp 356, Gly 304, His 299, and Glu 233 of α-amylase, forms salt bridges with His 305, Asp 197, and Glu 233 of α-amylase, forms hydrophobic interactions with His 305, Ala 198, Trp 58, and Tyr 62 of α-amylase, and forms π-cation interaction with Tyr 62 of α-amylase. In addition, QQQQLLR forms hydrogen bonds with residues Asp 62, Gly 228, His 332, and Gly 399 of α-glucosidase, forms salt bridges with Asp 202, Asp 333, and Glu 271 of α-glucosidase, and forms hydrophobic interactions with Phe 166, Tyr 389, Arg 400, Val 334, Phe 297, Phe 397, and Glu 231 of α-glucosidase (from FIG. 4C to FIG. 4D). Next, the binding force between α-amylase and peptide fragment KTGSGAEGMHGGK was first analyzed, as shown from FIG. 5A to FIG. 5B. Peptide fragment KTGSGAEGMHGGK forms hydrophobic interactions with residues Trp 284 and Tyr62 of α-amylase. In addition, residues Lys 200, Lys 225, Lys 261, and Gly 283 of α-amylase are all linked to KTGSGAEGMHGGK through hydrogen bonds. In addition to the hydrophobic interactions and hydrogen bonds, π-π stacking is formed between residue His 201 of α-amylase and peptide fragment KTGSGAEGMHGGK, while residue Trp284 of α-amylase is linked to peptide fragment KTGSGAEGMHGGK by π-cation interaction. In addition, His 101, Glu 233, and Glu 272 of α-amylase form salt bridges, i.e., ionic bonds, with peptide fragment KTGSGAEGMHGGK. As shown from FIG. 5C to FIG. 5D, KTGSGAEGMHGGK forms hydrophobic interactions with residues Trp 237 and Lys 221 of α-glucosidase. In addition, residues Gly 399, Lys 225, and Ala 343 of α-glucosidase are all linked to KTGSGAEGMHGGK through hydrogen bonds. In addition to hydrophobic interactions and hydrogen bonds, peptide fragment KTGSGAEGMHGGK forms a salt bridge, i.e., ionic bond, with residue Arg 429 of α-glucosidase. Finally, the interaction between peptide fragment KAHAALGAK and α-amylase was analyzed, as shown from FIG. 6A to FIG. 6B. Peptide fragment KAHAALGAK forms hydrophobic interactions with residues Leu 235, Ala 198, Leu 165, Tyr 62, Ile 51, and Trp 59 of α-amylase, and forms two hydrogen bonds with residues Gln 63 and Thr 163 of α-amylase, forms a salt bridge (i.e., ionic bond) with residue Glu 240 of α-amylase, and is linked to residue His 201 of α-amylase by π-π stacking interaction. Then, the interaction between peptide fragment KAHAALGAK and α-glucosidase was analyzed, as shown from FIG. 6C to FIG. 6D. KAHAALGAK forms hydrophobic interactions with residues Glu 377, Thr 339, Val 334, Val 335, Phe 397, and Ala 224 of α-glucosidase, forms four hydrogen bonds with residues Arg 429, Asn 301, Lys 225, and Gly 222 of α-glucosidase, and forms a salt bridge with residue Asp 379 of α-glucosidase. The stability of QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK was evaluated through EXPASY platform (http://web.expasy.org/protparam/). The ADMET properties of QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK were predicted through admetSAR (http://lmmd.ecust.edu.cn/admetsar1/predict/), mainly including human intestinal absorption (HIA) and acute oral toxicity. The results are shown in Table 3 and reveal that the six small peptides have low toxicity, and the three peptides of KTGSGAEGMHGGK, KAHAALGAK, and FALQGAAFLGSA have good in vitro stability, while the three peptides of QQLRPF, KTGSGAEGMHGGK, and KAHAALGAK have good HIA properties. In addition, except for FALQGAAFLGSA being hydrophobic and acidic, QQLRPF, AGAGPQGRP, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK are hydrophilic and alkaline, and AGAGPQGRP has a long half-life period.

TABLE 3 In vitro function prediction analysis of the peptide fragments of QQLRPF, AGAGPQGRP, FALQGAAFLGSA, QQQQLLR, KTGSGAEGMHGGK, and KAHAALGAK Half− Molecular In Theoretical life weight vitro hydrophilicity/ isoelectric period SEQ ID NO: Peptide sequence (Da) HIA stability toxicity hydrophobicity point (hour) 1 QQLRPF 787.92 + 136.73 III −1.083 9.75 0.8 5 KTGSGAEGMHG 1216.33 + 35.22 III −1.1 8.6 1.3 GK 6 KAHAALGAK 866.03 + −9.98 III −0.04 10 1.3 3 FALQGAAFLGSA 1152.32 − 29.26 III 1.275 5.52 1.1 2 AGAGPQGRP 809.88 − 42.26 III −0.978 9.79 4.4 4 QQQQLLR 913.04 − 118.63 III −1.557 9.75 0.8

Embodiment 6: Determination of In Vitro α-Amylase and α-Glucosidase Inhibitory Activity of Peptide Fragments Screened from Millet Prolamin

The method for determining α-amylase activity is as follows: 500 μL of sample (0.5%) and 500 μL of 0.02 mol/L sodium phosphate buffer (pH=6.9, 0.006 mol/L NaCl, and including α-amylase solution (13 U/mL)) were incubated at 25° C. for 10 min. After the pre-incubation, 500 μL of 1% soluble starch solution (0.02 mol/L sodium phosphate buffer, pH=6.9, and 0.006 mol/L NaCl) was added, followed by incubation at 25° C. for 10 min and adding 1.0 mL of dinitrosalicylic acid (DNS) reagent. Then, the resulting solution was boiled in a boiling water bath for 5 min, followed by stopping the reaction and cooling to room temperature. The reaction solution was diluted with 10 mL of distilled water and readed at 540 nm. For the control, deionized water was used to replace the sample. The calculation formula is as follows:

${\alpha - {{amylase}{inhibition}{{rate}{}(\%)}}} = {\frac{{A{control}} - {A{sample}}}{A{control}} \times 100\%}$

The method for determining α-glucosidase activity is as follows: First, the solution of substrate 4-Nitrophenyl β-D-glucopyranoside (PNPG) with a concentration of 1.505 mg/mL (5 mmol/L of PNPG dissolved in 0.1 mol/L phosphate buffer with a pH of 6.8) was prepared, a Na₂CO₃ solution with a concentration of 0.2 mol/L was prepared, and α-glucosidase solution (0.8 U/ml of α-glucosidase dissolved in 0.1 mol/L phosphate buffer with a pH of 6.8) was prepared. After the solutions were prepared, the following two groups were set for determination:

Add amount (μL) Sample group (0.5%) Control group Phosphate buffer 50 70 Sample 20 — PNPG solution 20 20

After preparing according to the above table, the resulting solution was shaken in a water bath at 37° C. for 10 min, followed by adding 100 μL of enzyme solution and continuing to shake in the water bath at 37° C. for 10 min. Finally, 50 μL of Na₂CO₃ solution was added, and the absorbance was measured at 405 nm. The formula for calculating the α-glucosidase inhibition rate is as follows:

${\alpha - {{glucosidase}{inhibition}{rate}}}{} = {\frac{{A{control}} - {A{sample}}}{A{control}} \times 100\%}$

The results are shown in FIG. 7 and it can be seen that the α-glucosidase inhibition rates of QQLRPF and AGAGPQGRP are 32.67% and 31.57%, respectively, which are significantly higher than those of KTGSGAEGMHGGK, KAHAALGAK, FALQGAAFLGSA, and QQQQLLR. The α-glucosidase inhibition rate of FALQGAAFLGSA is 17.67%, which is significantly higher than those of KTGSGAEGMHGGK (15.64%), KAHAALGAK (13.77%), and QQQQLLR (15.94%), while KAHAALGAK has the lowest α-glucosidase inhibition rate. As shown in FIG. 8 , the α-amylase inhibition rate of QQLRPF is 42.67%, which is the highest and followed by AGAGPQGRP (37.67%), FALQGAAFLGSA (24.42%), KTGSGAEGMHGGK (15.66%), KAHAALGAK (15.42%), and QQQQLLR (16.99%). 

What is claimed is:
 1. A cooked millet prolamin peptide for inhibiting a α-amylase and a α-glucosidase, wherein a sequence of the cooked millet prolamin peptide is selected from SEQ ID NOS: 1-6.
 2. The cooked millet prolamin peptide according to claim 1, wherein the sequence of the cooked millet prolamin peptide is shown in SEQ ID NO: 1 or SEQ ID NO:
 2. 3. A composition, comprising the cooked millet prolamin peptide according to claim 1 and an acceptable excipient for pharmaceutical products, food products, or health products.
 4. A method for an application of the cooked millet prolamin peptide according to claim 1 in preparing hypoglycemic drugs, food products, or health products suitable for a diabetic population.
 5. The application according to claim 4, wherein diabetes is type 2 diabetes.
 6. The composition according to claim 3, wherein the sequence of the cooked millet prolamin peptide is shown in SEQ ID NO: 1 or SEQ ID NO:
 2. 7. The method for the application of the cooked millet prolamin peptide according to claim 4, wherein the sequence of the cooked millet prolamin peptide is shown in SEQ NO: 1 or SEQ ID NO:
 2. 8. A method for an application of the composition according to claim 3 in preparing hypoglycemic drugs, food products, or health products suitable for a diabetic population. 